DP-PCA: Statistically Optimal and Differentially Private PCA
We study the canonical statistical task of computing the principal component from $n$ i.i.d.~data in $d$ dimensions under $(\varepsilon,δ)$-differential privacy. Although extensively studied in literature, existing solutions fall short on two key aspects: ($i$) even for Gaussian data, existing private algorithms require the number of samples $n$ to ...
Xiyang Liu +3 more
openaire +3 more sources
Perceived self-efficacy on advance care planning in Latin America: ACP-SEs Latam validation
IntroductionAdvance Care Planning is a fundamental process in palliative and person-centered care, as it promotes clinical decisions that align with patients’ values and preferences.
Patricia Bonilla +9 more
doaj +1 more source
A Model for Identifying Road Risk Class
In many road safety, traffic management, and travel planning analyses, it is useful to classify road sections according to risk level. Such classification is labour-intensive and needs to be reviewed periodically.
Ryguła Artur +2 more
doaj +1 more source
Landslide Hazard Analysis Using a Multilayered Approach Based on Various Input Data Configurations
Landslide is a natural disaster that occurs mostly in hill areas. Landslide hazard mapping is used to classify the prone areas to mitigate the risk of landslide hazards.
Ilyas Ahmad Huqqani +2 more
doaj +1 more source
Mamba-Enhanced Background Suppression Diffusion Model for Hyperspectral Anomaly Detection
Hyperspectral anomaly detection (HAD) faces a significant challenge in separating scarce, small and subtle anomalous targets from complex backgrounds.
Dan Sun, Shengwei Zhong, Chen Gong
doaj +1 more source
A survey on deep learning for polyp segmentation: techniques, challenges and future trends
Early detection and assessment of polyps play a crucial role in the prevention and treatment of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist clinicians in accurately locating and segmenting polyp regions.
Jiaxin Mei +6 more
doaj +1 more source
Hybrid modeling and prediction of oyster norovirus outbreaks
This paper presents a hybrid model for predicting oyster norovirus outbreaks by combining the Artificial Neural Networks (ANNs) and Principal Component Analysis (PCA) methods and using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite ...
Shima Shamkhali Chenar, Zhiqiang Deng
doaj +1 more source
Structural insights into an engineered feruloyl esterase with improved MHET degrading properties
A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa +5 more
wiley +1 more source
Detecting nearshore underwater targets in hyperspectral imagery faces significant challenges due to complex background clutter, weak and distorted underwater target signals. Extracting discriminative features is a critical step. Current methods are often
Mengxin Liu, Shengwei Zhong
doaj +1 more source
Development and Evaluation of an Electronic Nose System Based on MOS Sensors to Detect and to Distinguish Lemon Essential Oils [PDF]
Introduction Essences or essential oils are aromatic compounds that are found in different organs of the plants. Essences can be classified into three groups of natural, synthetic and natural like.
P Fayyaz +3 more
doaj +1 more source

